Carbon sink statistical method and system based on nori cultivation carbon sink potential monitoring and evaluation

Abstract

The invention discloses a carbon sink statistical method and system based on nori cultivation carbon sink potential monitoring and evaluation. The method comprises the steps that environmental parameter data are collected in real time through a multi-parameter sensor array deployed in a cultivation area; constructing a carbon flux evaluation model by combining nori culture biomass; simulating a migration and transformation process of carbon elements in'frond-water-sediment 'through a three-dimensional carbon transfer path tracking algorithm to obtain a three-dimensional carbon flux dynamic matrix; constructing a carbon sink space-time distribution model, and correcting the carbon sink space-time distribution in combination with the environmental data of the laver culture area; carbon element accumulation curves of different time dimensions are extracted, and a carbon sink potential evaluation function is constructed in combination with the growth cycle of the laver; and establishing a grading judgment system, and constructing a three-level carbon sink capacity grade and a corresponding environmental parameter threshold combination thereof. The method has the advantages that the carbon adsorption potential of the laver culture area is accurately evaluated through real-time environment data acquisition, carbon flux evaluation, three-dimensional path simulation and spatial-temporal distribution correction.

Description

Technical Field

[0001] The present invention relates to contract optimization and early warning, and particularly to a carbon sink statistical method and system based on the monitoring and evaluation of the carbon sink potential of laver cultivation. Background Art

[0002] The monitoring and evaluation of the carbon sink potential of laver cultivation is to evaluate the absorption and fixation ability of laver cultivation on atmospheric carbon dioxide through scientific carbon sink statistical methods. Laver cultivation not only has a high efficiency in carbon dioxide absorption, but also can improve water quality and promote the sustainable development of the marine ecological environment. By regularly monitoring the growth situation and carbon sink capacity of laver cultivation areas, it can provide data support for the government and enterprises to formulate carbon trading policies and carbon emission reduction targets.

[0003] Currently, the carbon sink statistical methods and systems based on the monitoring and evaluation of the carbon sink potential of laver cultivation usually rely on relatively simple carbon flux estimation models, lacking a comprehensive modeling of the complex ecological processes in laver cultivation areas, especially in the migration and transformation of carbon elements between different environmental media. Many methods do not fully consider the carbon cycling processes in water bodies and sediments, resulting in poor accuracy and dynamics of carbon sink evaluation results. In addition, existing methods usually lack the function of real-time environmental parameter monitoring, and fail to correct the carbon sink amount in a timely manner in combination with environmental changes, often unable to reflect the carbon sink changes in laver cultivation areas in different seasons or growth cycles. Some methods lack accurate modeling of three-dimensional carbon transfer paths and spatio-temporal distributions, resulting in relatively rough evaluation results and being difficult to support high-precision carbon credit trading or ecological environment management decisions. Summary of the Invention

[0004] In order to improve the existing methods and systems, a carbon sink statistical method and system based on the monitoring and evaluation of the carbon sink potential of laver cultivation are provided. This method accurately evaluates the carbon sequestration potential of laver cultivation areas through real-time environmental data collection, carbon flux assessment, three-dimensional path simulation, and spatio-temporal distribution correction, and constructs a hierarchical determination system based on the evaluation results to provide scientific support for green development.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows: A carbon sink statistical method based on the monitoring and evaluation of the carbon sink potential of laver cultivation, comprising: Real-time collecting environmental parameter data through a multi-parameter sensor array deployed in the cultivation area; Based on the environmental parameter data and combined with the laver cultivation biomass, constructing a carbon flux assessment model, the carbon flux assessment model including: calculating the photosynthetic carbon fixation rate based on the photosynthesis process of laver, calculating the respiration release rate based on the laver biomass and the plant respiration model, and calculating the organic carbon decomposition rate based on the change of laver biomass and environmental data combined with the organic decomposition model; Based on the photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate obtained from the carbon flux assessment model, the three-dimensional carbon transfer path tracking algorithm is used to simulate the migration and transformation process of carbon elements in the "algae body - water - sediment", and a three-dimensional carbon flux dynamic matrix is obtained; Based on the three-dimensional carbon flux dynamic matrix, a spatio-temporal distribution model of carbon sink quantity is constructed, and combined with the environmental data of the laver cultivation area, the spatio-temporal distribution of carbon sink quantity is corrected; Based on the corrected spatio-temporal distribution model of carbon sink quantity, the cumulative curve of carbon elements in different time dimensions is extracted, and combined with the growth cycle of laver, a carbon sink potential evaluation function is constructed; Based on the output value of the carbon sink potential evaluation function, a hierarchical determination system is established, and a three-level carbon sink capacity level and its corresponding combination of environmental parameter thresholds are constructed.

[0006] Preferably, based on the environmental parameter data and combined with the laver cultivation biomass, a carbon flux assessment model is constructed. The carbon flux assessment model includes: calculating the photosynthetic carbon fixation rate based on the photosynthesis process of laver, calculating the respiratory release rate based on the laver biomass and the plant respiration model, and calculating the organic carbon decomposition rate based on the change of laver biomass and environmental data combined with the organic decomposition model. Specifically, it includes: Based on the process of laver decomposing organic matter to release carbon dioxide, a photosynthesis rate model is constructed to calculate and obtain the photosynthetic carbon fixation rate; Combined with the laver biomass and the Q10 model of plant respiration, the respiratory release rate is calculated and obtained; Based on the change of laver biomass and environmental data, combined with the ecological organic decomposition model, the organic carbon decomposition rate is calculated and obtained; The photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate are integrated to construct a comprehensive carbon flux assessment model.

[0007] Preferably, the photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate obtained from the carbon flux assessment model are used to simulate the migration and transformation process of carbon elements in the "algae body - water - sediment" through the three-dimensional carbon transfer path tracking algorithm to obtain the three-dimensional carbon flux dynamic matrix. Specifically, it includes: Based on the spatial scope of the laver cultivation area, the algae body area, water area, and sediment area to be simulated are determined, and a three-dimensional space model is constructed; The source of carbon is defined, and different transformation and migration processes of carbon are obtained based on the carbon migration in laver organisms and the carbon cycle in sediments; The three-dimensional space model is divided into multiple cells. Based on each cell, according to the transformation and migration process of carbon elements, the carbon path of carbon elements in the "algae body - water - sediment" is simulated through the path tracking algorithm and modeled; According to the division of the three-dimensional space, a carbon flux matrix for each cell is constructed, including the inflow and outflow of carbon for each cell; Obtain a three-dimensional carbon flux dynamic matrix based on the dynamic flux changes of carbon elements in each grid cell.

[0008] Preferably, constructing a spatio-temporal distribution model of carbon sink volume based on the three-dimensional carbon flux dynamic matrix, and combining the environmental data of the laver cultivation area to correct the spatio-temporal distribution of carbon sink volume specifically includes: Based on the three-dimensional carbon flux dynamic matrix, obtain the dynamic time series data of the three-dimensional carbon flux according to the periodic changes in the cultivation area; Based on the inflow and outflow of carbon in each cell of the three-dimensional space model of the cultivation area, obtain the spatial distribution data of carbon elements; Based on the dynamic time series data of the three-dimensional carbon flux and the spatial distribution data of carbon elements, construct a spatio-temporal distribution model of carbon sink volume by calculating the carbon sink volume; Based on the real-time collected environmental parameter data, according to the environmental characteristics of different regions, adjust the calculation of the carbon sink volume in each cell in the model, and combine the seasonal change data to adjust the change curve of the carbon sink volume over time in the model to correct the spatio-temporal distribution model of carbon sink volume.

[0009] Preferably, extracting the cumulative curves of carbon elements in different time dimensions based on the corrected spatio-temporal distribution model of carbon sink volume, and constructing a carbon sink potential evaluation function in combination with the laver growth cycle specifically includes: Based on the corrected spatio-temporal distribution model of carbon sink volume, statistically analyze the carbon sink volume output by the model in different time dimensions, and calculate the total carbon fixation amount in the laver cultivation area for each time period to obtain carbon accumulation data; Based on the carbon accumulation data, construct the cumulative curves of carbon elements in different time dimensions and smooth the cumulative curves; Based on each growth cycle of the laver, obtain the photosynthesis rate, respiration release rate and carbon fixation efficiency at each stage; Combined with the growth rate, environmental factors and biomass of the laver at each stage, construct a carbon sink potential evaluation function, and optimize the parameters in the function according to historical data and on-site measurement results.

[0010] Preferably, establishing a hierarchical determination system based on the output value of the carbon sink potential evaluation function, and constructing a three-level carbon sink capacity level and its corresponding combination of environmental parameter thresholds specifically includes: Construct a three-level carbon sink capacity level based on the output value of the carbon sink potential evaluation function, including high capacity, medium capacity and low capacity; Based on each level of carbon sink capacity level, set a combination of environmental parameter thresholds to form a hierarchical determination system.

[0011] Furthermore, a carbon sink statistics system based on the monitoring and evaluation of the carbon sink potential of laver cultivation is proposed, including: Environmental parameter acquisition module: The environmental parameter acquisition module collects environmental parameter data of the laver cultivation area in real time by deploying a multi-parameter sensor array; Carbon flux assessment module: The carbon flux assessment module is used to construct a carbon flux assessment model by combining environmental parameter data and laver biomass, and obtain the photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate; Carbon transfer path module: The carbon transfer path module simulates the migration and transformation process of carbon elements in "algae body - water - sediment" through a three-dimensional carbon transfer path tracking algorithm, and obtains a three-dimensional carbon flux dynamic matrix; Carbon sink amount spatio-temporal distribution module: The carbon sink amount spatio-temporal distribution module constructs and corrects a spatio-temporal distribution model of the carbon sink amount based on the three-dimensional carbon flux dynamic matrix and combines environmental data; Carbon sink potential assessment module: The carbon sink potential assessment module extracts the cumulative curve of carbon elements based on the corrected spatio-temporal distribution model of the carbon sink amount, and constructs a carbon sink potential assessment function in combination with the laver growth cycle; Carbon sink capacity classification and determination module: The carbon sink capacity classification and determination module establishes a three-level classification system for the carbon sink capacity based on the output value of the carbon sink potential assessment function, and corresponds to the environmental parameter threshold combination; Processor: The processor is used to process the calculation process of each formula and the construction and calculation process of each model.

[0012] Compared with the prior art, the advantages of the present invention are as follows: By collecting environmental parameter data in real time and combining laver biomass, a carbon flux assessment model is constructed, which can accurately calculate the photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate, and comprehensively reflect the carbon sequestration and release process in the laver cultivation area. Using a three-dimensional carbon transfer path tracking algorithm to simulate the dynamic migration and transformation of carbon elements in "algae body - water - sediment" can further accurately obtain the spatio-temporal distribution characteristics of carbon flux. In addition, correcting the carbon sink amount in combination with environmental data helps to improve the timeliness and accuracy of the model. By extracting the cumulative curve of carbon elements in different time dimensions and combining the growth cycle of laver, a carbon sink potential assessment function is constructed, realizing the scientific assessment of the carbon sink potential in the laver cultivation area. Finally, through the classification and determination system, different carbon sink capacity levels are delimited according to the carbon sink potential assessment results, providing a clear environmental parameter threshold combination. Brief Description of the Drawings

[0013] Figure 1 It is a schematic diagram of the method proposed by the present invention; Figure 2 It is a schematic diagram of the carbon flux assessment model proposed by the present invention; Figure 3 It is a schematic diagram of the three-dimensional carbon flux dynamic matrix proposed by the present invention; Figure 4 Schematic diagram of the spatio-temporal distribution model of carbon sink volume proposed by the present invention; Figure 5 Schematic diagram of the carbon sink potential evaluation function proposed by the present invention; Figure 6 Schematic diagram of the hierarchical determination system proposed by the present invention; Figure 7 Architecture diagram of the electronic device in this solution; Figure 8 Schematic diagram of the structure of the computer-readable storage medium in this solution. Specific implementation manners

[0014] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variants.

[0015] A carbon sink statistical system based on the monitoring and evaluation of the carbon sink potential of laver cultivation, comprising: Environmental parameter acquisition module: The environmental parameter acquisition module collects environmental parameter data of the laver cultivation area in real time by deploying a multi-parameter sensor array; Carbon flux evaluation module: The carbon flux evaluation module is used to combine environmental parameter data and laver biomass to construct a carbon flux evaluation model, and obtain the photosynthetic carbon fixation rate, respiration release rate, and organic carbon decomposition rate; Carbon transfer path module: The carbon transfer path module simulates the migration and transformation process of carbon elements in "algae body - water body - sediment" through a three-dimensional carbon transfer path tracking algorithm, and obtains a three-dimensional carbon flux dynamic matrix; Carbon sink volume spatio-temporal distribution module: The carbon sink volume spatio-temporal distribution module constructs and corrects the spatio-temporal distribution model of the carbon sink volume based on the three-dimensional carbon flux dynamic matrix and combines environmental data; Carbon sink potential evaluation module: The carbon sink potential evaluation module extracts the cumulative curve of carbon elements based on the corrected spatio-temporal distribution model of the carbon sink volume, and constructs a carbon sink potential evaluation function in combination with the laver growth cycle; Carbon sink capacity grading determination module: The carbon sink capacity grading determination module establishes a three-level grading system for the carbon sink capacity based on the output value of the carbon sink potential evaluation function, and corresponds to the environmental parameter threshold combination; Processor: The processor is used to process the calculation process of each formula and the construction calculation process of each model.

[0016] Refer to Figure 1 As shown, a carbon sink statistical method based on the monitoring and evaluation of the carbon sink potential of laver cultivation, comprising: Step 1: Collect environmental parameter data in real time through a multi-parameter sensor array deployed in the cultivation area; Step 2: Based on the environmental parameter data and combined with the biomass of laver cultivation, construct a carbon flux assessment model. The carbon flux assessment model includes: calculating the photosynthetic carbon fixation rate based on the photosynthesis process of laver, calculating the respiratory release rate based on the laver biomass and the plant respiration model, and calculating the organic carbon decomposition rate based on the change of laver biomass and environmental data combined with the organic decomposition model; Step 3: Based on the photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate obtained from the carbon flux assessment model, simulate the migration and transformation process of carbon elements in the "algae body - water body - sediment" through a three-dimensional carbon transfer path tracking algorithm to obtain a three-dimensional carbon flux dynamic matrix; Step 4: Based on the three-dimensional carbon flux dynamic matrix, construct a spatio-temporal distribution model of carbon sink volume, and combine it with the environmental data of the laver cultivation area to correct the spatio-temporal distribution of carbon sink volume; Step 5: Based on the corrected spatio-temporal distribution model of carbon sink volume, extract the cumulative curve of carbon elements in different time dimensions, and combine it with the growth cycle of laver to construct a carbon sink potential assessment function; Step 6: Establish a hierarchical determination system based on the output value of the carbon sink potential assessment function, and construct a three-level carbon sink capacity level and its corresponding combination of environmental parameter thresholds.

[0017] Refer to Figure 2 As shown, based on the environmental parameter data and combined with the biomass of laver cultivation, construct a carbon flux assessment model. The carbon flux assessment model includes: calculating the photosynthetic carbon fixation rate based on the photosynthesis process of laver, calculating the respiratory release rate based on the laver biomass and the plant respiration model, and calculating the organic carbon decomposition rate based on the change of laver biomass and environmental data combined with the organic decomposition model specifically includes: Construct a photosynthesis rate model based on the process of laver decomposing organic matter to release carbon dioxide, and calculate and obtain the photosynthetic carbon fixation rate; Combine the laver biomass and the Q10 model of plant respiration to calculate and obtain the respiratory release rate; Based on the change of laver biomass and environmental data, combined with the ecological organic decomposition model, calculate and obtain the organic carbon decomposition rate; Integrate the photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate to construct a comprehensive carbon flux assessment model.

[0018] Specifically, the photosynthesis rate is the rate at which laver fixes carbon dioxide through photosynthesis, and the formula is: ; Among them, is the photosynthesis rate, is a function of photosynthetically active radiation, usually related to the environmental light intensity, and this function can be represented by a linear or exponential function , where is the photosynthetically active radiation, is the light saturation constant, reflecting the light absorption ability of Porphyra, is the photosynthesis efficiency; The respiratory release rate of Porphyra is the amount of carbon dioxide released by the respiration of plants. The respiration rate of plants changes with temperature, and the Q10 model is commonly used to represent this relationship. The formula is: ; where, is the respiration rate at temperature T, is the respiration rate at the reference temperature , and Q10 is the influence coefficient of temperature on the respiration rate; The calculation of the respiratory release rate involves the influence of Porphyra biomass and temperature. By combining the biomass of Porphyra with the Q10 model, the respiratory release rate of Porphyra is obtained; The organic carbon decomposition rate describes the rate at which organic matter in Porphyra releases carbon dioxide during the decomposition process. This process is usually affected by factors such as temperature, humidity, Porphyra biomass, and microbial activity; Integrate the photosynthesis rate, respiratory release rate, and organic carbon decomposition rate to build a comprehensive carbon flux model.

[0019] Refer to Figure 3 As shown, based on the photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate obtained from the carbon flux assessment model, the migration and transformation process of carbon elements in the "algae body - water - sediment" is simulated through a three-dimensional carbon transfer path tracking algorithm. The specific content of the three-dimensional carbon flux dynamic matrix includes: Based on the spatial range of the Porphyra cultivation area, determine the algae body area, water area, and sediment area to be simulated, and construct a three-dimensional space model; Define the source of carbon, and obtain different conversion and migration processes of carbon based on the carbon migration in Porphyra organisms and the carbon cycle in sediments; Divide the three-dimensional space model into multiple cells. Based on each cell, according to the conversion and migration process of carbon elements, simulate the carbon path of carbon elements in the "algae body - water - sediment" through the path tracking algorithm and build a model; According to the division of the three-dimensional space, construct the carbon flux matrix of each cell, including the inflow and outflow of carbon in each cell; Based on the dynamic flux changes of carbon elements in each grid cell, obtain the three-dimensional carbon flux dynamic matrix.

[0020] Specifically, the thallus area refers to the water area where laver grows, including the laver organism and its directly affected area. The water body area refers to the water layer part in the water area where laver grows, mainly involving the transport and exchange of dissolved organic matter and carbon dioxide. The sediment area refers to the sediment layer at the bottom of the water body, mainly involving the decomposition and accumulation processes of organic carbon; The sources of carbon include photosynthesis: laver absorbs carbon dioxide from water and fixes it into organic matter; plant respiration: the metabolic process of laver itself releases carbon dioxide; decomposition of organic carbon: the decomposition of laver and other organic substances in the sediment releases carbon dioxide; The processes of carbon transformation and migration include: carbon transformation in the thallus: laver fixes carbon dioxide through photosynthesis and releases carbon dioxide through respiration; carbon exchange in the water body: the exchange of carbon dioxide between the water body and the atmosphere and the dissolution and release of organic carbon in the water body; carbon cycle in the sediment: the decomposition of organic matter in the sediment releases carbon dioxide, and organic carbon is redeposited; Using the path tracing algorithm to simulate the migration process of carbon in the "thallus-water body-sediment", in each cell, according to the sources and transformation processes of carbon, the migration of carbon can be expressed by the following formula: ; where, is the carbon content in cell , is the inflow of carbon in this cell, is the outflow of carbon in this cell; According to the path tracing algorithm, obtain the sources and flow directions of carbon, and simulate the transformation process of carbon between different regions; According to the migration and transformation processes of carbon, establish a carbon flux matrix in each grid cell. The carbon flux matrix of each grid cell includes the inflow and outflow of carbon, and construct a three-dimensional carbon flux dynamic matrix.

[0021] Refer to Figure 4 As shown, based on the three-dimensional carbon flux dynamic matrix, construct a spatio-temporal distribution model of carbon sink volume, and combine with the environmental data of the laver cultivation area to correct the spatio-temporal distribution of carbon sink volume, specifically including: Based on the three-dimensional carbon flux dynamic matrix, according to the periodic changes in the cultivation area, obtain the dynamic time series data of the three-dimensional carbon flux; Based on the inflow and outflow of carbon in each cell of the three-dimensional space model of the cultivation area, obtain the spatial distribution data of carbon elements; Based on the dynamic time series data of the three-dimensional carbon flux and the spatial distribution data of carbon elements, construct a spatio-temporal distribution model of carbon sink volume by calculating the carbon sink volume; Based on the real-time collected environmental parameter data, according to the environmental characteristics of different regions, adjust the calculation of the carbon sink amount of each cell in the model, and combine the seasonal change data to adjust the change curve of the carbon sink amount over time in the model, and correct the spatio-temporal distribution model of the carbon sink amount.

[0022] Specifically, obtain the carbon flux of each grid cell at different time steps through the aforementioned three-dimensional carbon flux matrix, and model it through time series data; according to the dynamic time series data of the three-dimensional carbon flux, obtain the carbon inflow and outflow of each grid cell, and discretize the dynamic change of carbon in space through numerical methods to obtain the distribution of carbon elements in three-dimensional space; Calculate the carbon sink amount according to the carbon flux in each grid cell. The carbon sink amount is the accumulation amount of carbon in a certain spatial area per unit time. By synthesizing the data of time series and spatial distribution, construct a spatio-temporal distribution model of the carbon sink amount, and correct the calculation of the carbon sink amount of each cell based on the real-time collected environmental parameter data.

[0023] Seasonal changes can adjust the change of the carbon sink amount over time by adding a seasonal correction factor, and the formula is; ; where, is the seasonal correction factor, is a periodic function, reflecting the influence of seasonal changes.

[0024] Refer to Figure 5 As shown, based on the corrected spatio-temporal distribution model of the carbon sink amount, extract the carbon element accumulation curves in different time dimensions, and construct a carbon sink potential evaluation function in combination with the growth cycle of laver, which specifically includes: Based on the corrected spatio-temporal distribution model of the carbon sink amount, statistically analyze the carbon sink amount output by the model according to different time dimensions, and calculate the total fixed amount of carbon in the laver cultivation area for each time period to obtain carbon accumulation data; Based on the carbon accumulation data, construct carbon element accumulation curves in different time dimensions and smooth the accumulation curves; Based on the growth cycles of laver, obtain the photosynthesis rate, respiration release rate and carbon fixation efficiency of each stage; Combine the growth rate, environmental factors and biomass of laver at each stage to construct a carbon sink potential evaluation function, and optimize the parameters in the function according to historical data and field measurement results.

[0025] Specifically, carbon sink data is extracted from the calibrated spatio-temporal distribution model of carbon sink. These data represent the carbon sink of each grid cell at different time points. The carbon sink data is statistically analyzed according to different time dimensions, and the change of carbon accumulation data over time is plotted as a carbon accumulation curve, which shows the carbon accumulation in the laver cultivation area during different time periods; The photosynthesis rate is the rate at which laver fixes carbon dioxide through photosynthesis during its growth period. A photosynthesis rate model can be established based on environmental parameters such as light intensity, temperature, laver biomass, and the photosynthesis characteristics of laver. The respiration rate of laver is the rate of carbon dioxide release during its metabolic activities. The carbon fixation efficiency represents the ratio between the amount of carbon fixed by laver through photosynthesis and the amount of carbon released by its respiration; According to the growth cycle of laver, environmental factors such as light, temperature, nutrient concentration, etc., and biomass, a carbon sink potential assessment function is constructed. Through historical data and field measurement results, the parameters in the carbon sink potential assessment function are optimized. The optimized carbon sink potential assessment function can more accurately predict the carbon absorption and carbon sequestration capabilities of the laver cultivation area under different environmental and management conditions.

[0026] Refer to Figure 6 As shown, a hierarchical determination system is established based on the output value of the carbon sink potential assessment function. The construction of the three-level carbon sink capacity level and its corresponding combination of environmental parameter thresholds specifically includes: Based on the output value of the carbon sink potential assessment function, a three-level carbon sink capacity level is constructed, including high capacity, medium capacity, and low capacity; Based on each level of carbon sink capacity level, a combination of environmental parameter thresholds is set to form a hierarchical determination system.

[0027] Specifically, according to the output value of the carbon sink potential assessment function, the level of carbon sink capacity is determined. The carbon sink potential is divided into three levels. The first-level carbon sink capacity refers to the area with strong carbon sink potential, which can absorb and store a large amount of carbon; the second-level carbon sink capacity refers to the area with medium carbon sink potential, and the carbon absorption and storage capacity is average; the third-level carbon sink capacity refers to the area with weak carbon sink potential, and the carbon absorption and storage capacity is low; Light intensity has a greater impact on the photosynthesis of laver. High light intensity usually corresponds to higher carbon sink potential. Water temperature has an important impact on the growth rate and photosynthesis of laver. Appropriate water temperature usually increases the carbon sink potential. Moderate salinity and good water quality (low nitrogen and low phosphorus content) contribute to the healthy growth of laver, and thus improve the carbon sequestration ability; According to the specific data of environmental parameters, different threshold ranges are set, corresponding to the first-level, second-level, and third-level carbon sink capacities respectively. According to the measured environmental data and the output value of the carbon sink potential assessment function, the carbon sink capacity level of each area is determined in turn.

[0028] Further, the method according to the embodiments of the present application can also be implemented by means of Figure 7 the architecture of the electronic device shown. As Figure 7 shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store the carbon sink statistics method and system for monitoring and evaluating the carbon sink potential based on laver cultivation provided by the present application. The electronic device 500 may also include a terminal interface 508. Of course, Figure 7 the architecture shown is only exemplary. When implementing different devices, one or more components in the Figure 7 shown electronic device may be omitted according to actual needs.

[0029] Figure 8 FIG. is a schematic structural diagram of a computer-readable storage medium provided by an embodiment of the present application. As Figure 8 shown, it is a computer-readable storage medium 600 according to an embodiment of the present application. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are run by a processor, the carbon sink statistics method and system for monitoring and evaluating the carbon sink potential based on laver cultivation according to the embodiments of the present application described with reference to the above drawings can be executed. The storage medium 600 includes but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory, etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0030] It should be noted that: the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. And the above description of specific embodiments of this specification has been made. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0031] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments.

[0032] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A carbon sink statistical method based on the monitoring and evaluation of the carbon sink potential of laver cultivation, characterized in that, Including: Real-time collecting environmental parameter data through a multi-parameter sensor array deployed in the aquaculture area; Based on the environmental parameter data and combined with the biomass of laver aquaculture, constructing a carbon flux assessment model, which includes: calculating the photosynthetic carbon fixation rate based on the photosynthesis process of laver, calculating the respiration release rate based on the biomass of laver and the plant respiration model, and calculating the organic carbon decomposition rate based on the change of laver biomass and environmental data combined with the organic decomposition model; Based on the photosynthetic carbon fixation rate, respiration release rate, and organic carbon decomposition rate obtained from the carbon flux assessment model, simulating the migration and transformation process of carbon elements in the "algae body - water body - sediment" through a three-dimensional carbon transfer path tracking algorithm to obtain a three-dimensional carbon flux dynamic matrix; Constructing a spatio-temporal distribution model of carbon sink volume based on the three-dimensional carbon flux dynamic matrix, and correcting the spatio-temporal distribution of carbon sink volume in combination with the environmental data of the laver aquaculture area; Based on the corrected spatio-temporal distribution model of carbon sink volume, extracting the cumulative curve of carbon elements in different time dimensions, and constructing a carbon sink potential assessment function in combination with the growth cycle of laver; Establishing a hierarchical determination system based on the output value of the carbon sink potential assessment function, and constructing a three-level carbon sink capacity level and its corresponding combination of environmental parameter thresholds.

2. The carbon sink statistics method based on the monitoring and evaluation of the carbon sink potential of laver cultivation according to claim 1, wherein, The constructing of the carbon flux assessment model based on the environmental parameter data and combined with the biomass of laver aquaculture, which includes: calculating the photosynthetic carbon fixation rate based on the photosynthesis process of laver, calculating the respiration release rate based on the biomass of laver and the plant respiration model, and calculating the organic carbon decomposition rate based on the change of laver biomass and environmental data combined with the organic decomposition model specifically includes: Constructing a photosynthesis rate model based on the process of laver decomposing organic matter to release carbon dioxide, and calculating to obtain the photosynthetic carbon fixation rate; Combining the biomass of laver and the Q10 model of plant respiration, and calculating to obtain the respiration release rate; Based on the change of laver biomass and environmental data, combined with the ecological organic decomposition model, calculating to obtain the organic carbon decomposition rate; Integrating the photosynthetic carbon fixation rate, respiration release rate, and organic carbon decomposition rate to construct a comprehensive carbon flux assessment model.

3. The carbon sink statistical method based on the monitoring and evaluation of the carbon sink potential of laver cultivation according to claim 1, wherein, The simulating of the migration and transformation process of carbon elements in the "algae body - water body - sediment" through a three-dimensional carbon transfer path tracking algorithm based on the photosynthetic carbon fixation rate, respiration release rate, and organic carbon decomposition rate obtained from the carbon flux assessment model to obtain a three-dimensional carbon flux dynamic matrix specifically includes: Based on the spatial range of the laver aquaculture area, determining the algae body area, water body area, and sediment area to be simulated, and constructing a three-dimensional space model; Defining the source of carbon, and obtaining different transformation and migration processes of carbon based on the carbon migration in laver organisms and the carbon cycle in sediments; Dividing the three-dimensional space model into multiple cells, and based on each cell, simulating the carbon path of carbon elements in the "algae body - water body - sediment" through the path tracking algorithm and modeling according to the transformation and migration process of carbon elements; According to the division of the three-dimensional space, constructing a carbon flux matrix for each cell, including the inflow and outflow of carbon in each cell; Based on the dynamic flux change of carbon elements in each grid cell, obtaining a three-dimensional carbon flux dynamic matrix.

4. The carbon sink statistical method based on the monitoring and evaluation of the carbon sink potential of laver cultivation according to claim 1, wherein, Constructing a spatio-temporal distribution model of carbon sink volume based on a three-dimensional carbon flux dynamic matrix, and calibrating the spatio-temporal distribution of carbon sink volume by combining environmental data of the laver cultivation area specifically includes: Based on the three-dimensional carbon flux dynamic matrix, obtaining the dynamic time series data of the three-dimensional carbon flux according to the periodic changes in the cultivation area; Based on the inflow and outflow of carbon in each cell of the three-dimensional space model of the cultivation area, obtaining the spatial distribution data of carbon elements; Based on the dynamic time series data of the three-dimensional carbon flux and the spatial distribution data of carbon elements, constructing a spatio-temporal distribution model of carbon sink volume by calculating the carbon sink volume; Based on the real-time collected environmental parameter data, according to the environmental characteristics of different regions, adjusting the calculation of the carbon sink volume in each cell in the model, and combining seasonal change data, adjusting the change curve of the carbon sink volume over time in the model to calibrate the spatio-temporal distribution model of carbon sink volume.

5. The carbon sink statistical method based on the monitoring and evaluation of the carbon sink potential of laver cultivation according to claim 1, characterized in that, The method of extracting the cumulative curve of carbon elements in different time dimensions based on the calibrated spatio-temporal distribution model of carbon sink volume and constructing a carbon sink potential evaluation function by combining the laver growth cycle specifically includes: Based on the calibrated spatio-temporal distribution model of carbon sink volume, statistically analyzing the carbon sink volume output by the model in different time dimensions, and calculating the total fixed amount of carbon in the laver cultivation area for each time period to obtain carbon accumulation data; Based on the carbon accumulation data, constructing the cumulative curve of carbon elements in different time dimensions and smoothing the cumulative curve; Based on each growth cycle of the laver, obtaining the photosynthesis rate, respiration release rate, and carbon fixation efficiency at each stage; Combining the growth rate, environmental factors, and biomass of the laver at each stage, constructing a carbon sink potential evaluation function, and optimizing the parameters in the function according to historical data and field measurement results.

6. The carbon sink statistical method based on the monitoring and evaluation of the carbon sink potential of laver cultivation according to claim 1, wherein The method of establishing a hierarchical decision-making system based on the output value of the carbon sink potential evaluation function and constructing a three-level carbon sink capacity level and its corresponding environmental parameter threshold combination specifically includes: Constructing a three-level carbon sink capacity level based on the output value of the carbon sink potential evaluation function, including high capacity, medium capacity, and low capacity; Based on each level of carbon sink capacity level, setting the environmental parameter threshold combination to form a hierarchical decision-making system.

7. A carbon sink statistics system for monitoring and evaluating the carbon sink potential of laver cultivation, which is used to implement the carbon sink statistics method for monitoring and evaluating the carbon sink potential of laver cultivation according to any one of claims 1-6, characterized in that, Including: Environmental parameter acquisition module: The environmental parameter acquisition module collects the environmental parameter data of the laver cultivation area in real time by deploying a multi-parameter sensor array; Carbon flux evaluation module: The carbon flux evaluation module is used to construct a carbon flux evaluation model by combining environmental parameter data and laver biomass, and obtain the photosynthetic carbon fixation rate, respiration release rate, and organic carbon decomposition rate; Carbon transfer path module: The carbon transfer path module simulates the migration and transformation process of carbon elements in "algae body-water-sediment" through a three-dimensional carbon transfer path tracking algorithm to obtain a three-dimensional carbon flux dynamic matrix; Spatio-temporal distribution module of carbon sink volume: The spatio-temporal distribution module of carbon sink volume constructs and calibrates the spatio-temporal distribution model of carbon sink volume based on the three-dimensional carbon flux dynamic matrix and combines environmental data; Carbon sink potential evaluation module: The carbon sink potential evaluation module extracts the cumulative curve of carbon elements based on the calibrated spatio-temporal distribution model of carbon sink volume and constructs a carbon sink potential evaluation function by combining the laver growth cycle; Carbon sink capacity classification and determination module: The carbon sink capacity classification and determination module establishes a three-level classification system for carbon sink capacity based on the output value of the carbon sink potential evaluation function, and corresponds to the environmental parameter threshold combination; Processor: The processor is used to process the calculation process of each formula and the construction and calculation process of each model.

8. An electronic device, characterized in that, Comprising: At least one processor; And a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the carbon sink statistics method based on the monitoring and evaluation of the carbon sink potential of laver cultivation as described in any one of claims 1-6.

9. A computer-readable storage medium storing computer-readable instructions, characterized in that, When the computer-readable instructions are executed by the processor, the carbon sink statistics method based on the monitoring and evaluation of the carbon sink potential of laver cultivation as described in any one of claims 1-6 is implemented.

Images